Conference paper
Meta-Regression: A Framework for Robust Reactive Optimization
Maintaining optimal performance as the conditions of a system change is a challenging problem. To solve this problem, we present meta-regression, a general methodology for alleviating traditional difficulties in nonlinear regression modelling. Meta-regression allows for reactive optimization, in which system components self-organize to changing conditions in a manner that is robust, or affected minimally by other sources of variability.
Meta-regression extends profiling, providing a methodology for model-building when there is incomplete knowledge of the mechanisms and interactions of a nonlinear system.
| Language: | English |
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| Publisher: | IEEE Computer Society Press |
| Year: | 2007 |
| Pages: | 375-378 |
| Proceedings: | First IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007) |
| ISBN: | 0769529062 and 9780769529066 |
| Types: | Conference paper |
| DOI: | 10.1109/SASO.2007.37 |
| ORCIDs: | Kulahci, Murat |
Computer science Industrial engineering Maintenance engineering Mathematical model Nonlinear dynamical systems Nonlinear systems Polynomials Regression analysis Response surface methodology Robustness meta-regression nonlinear regression modelling nonlinear system optimisation regression analysis robust reactive optimization self-adjusting systems
